Decomposition algorithm for convex differentiable minimization
Journal of Optimization Theory and Applications
Asymptotic properties of the Fenchel dual functional and applications to decomposition problems
Journal of Optimization Theory and Applications
On the convergence of the coordinate descent method for convex differentiable minimization
Journal of Optimization Theory and Applications
Decomposition Methods for Differentiable Optimization Problems overCartesian Product Sets
Computational Optimization and Applications
Convergence of alternating optimization
Neural, Parallel & Scientific Computations
Convergent Decomposition Techniques for Training RBF Neural Networks
Neural Computation
Projected Gradient Methods for Nonnegative Matrix Factorization
Neural Computation
A convergent decomposition algorithm for support vector machines
Computational Optimization and Applications
A Parallel Nonnegative Tensor Factorization Algorithm for Mining Global Climate Data
ICCS 2009 Proceedings of the 9th International Conference on Computational Science
Outer approximation algorithms for canonical DC problems
Journal of Global Optimization
Multi-Standard Quadratic Optimization: interior point methods and cone programming reformulation
Computational Optimization and Applications
Solving low-rank matrix completion problems efficiently
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Fast coordinate descent methods with variable selection for non-negative matrix factorization
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
PADDLE: proximal algorithm for dual dictionaries learning
ICANN'11 Proceedings of the 21th international conference on Artificial neural networks - Volume Part I
Nonnegative factorization of diffusion tensor images and its applications
IPMI'11 Proceedings of the 22nd international conference on Information processing in medical imaging
Decomposition algorithms for generalized potential games
Computational Optimization and Applications
Efficient Nonnegative Matrix Factorization via projected Newton method
Pattern Recognition
Maximum Block Improvement and Polynomial Optimization
SIAM Journal on Optimization
Fast Nonnegative Matrix Factorization: An Active-Set-Like Method and Comparisons
SIAM Journal on Scientific Computing
A new necessary and sufficient global optimality condition for canonical DC problems
Journal of Global Optimization
Modified subspace Barzilai-Borwein gradient method for non-negative matrix factorization
Computational Optimization and Applications
Fast rank-2 nonnegative matrix factorization for hierarchical document clustering
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
A convergent algorithm for orthogonal nonnegative matrix factorization
Journal of Computational and Applied Mathematics
Multi-stage multi-task feature learning
The Journal of Machine Learning Research
A continuous characterization of the maximum-edge biclique problem
Journal of Global Optimization
Journal of Global Optimization
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We give new convergence results for the block Gauss-Seidel method for problems where the feasible set is the Cartesian product of m closed convex sets, under the assumption that the sequence generated by the method has limit points. We show that the method is globally convergent for m=2 and that for m2 convergence can be established both when the objective function f is componentwise strictly quasiconvex with respect to m-2 components and when f is pseudoconvex. Finally, we consider a proximal point modification of the method and we state convergence results without any convexity assumption on the objective function.